Bayes estimation under exponentially weighted minimum expected loss function from multiply Type-II censored Rayleigh data

Abstract

In this paper, we present a Bayesian approach to inference in reliability studies based on multiply Type-II censored data from a Rayleigh distribution using exponentially weighted minimum expected loss function. In this study, we have obtained Bayes estimator of the parameter, reliability and failure rate of the Rayleigh distribution. Highest posterior density and maximum likelihood estimators are also obtained. A simulated study is carried out to assess the performance of the estimators along with their maximum likelihood estimators under multiply Type-II censoring schemes.